Analysis of Tourists’ Image of Seoul with Geotagged Photos using Convolutional Neural Networks

Kim, Dongeun; Kang, Youngok; Park, Yearim; Kim, Nayeon; Lee, Juyoon; Cho, Nahye

In this study we aim to analyze the urban image of Seoul that tourists feel through the photos uploaded on Flickr, which is one of Social Network Service (SNS) platforms that people can share Geo-tagged photos. We first categorize the photos uploaded on the site by tourists and then performed the image mining by utilizing Convolutional Neural Network (CNN), which is one of the artificial neural networks with deep learning capability. In this study we are able to find out that tourists are interested in old palaces, historical monuments, stores, food, etc. in which are considered to be the signatured sightseeing elements in Seoul. Those key elements are differentiated from the major sightseeing attractions within Seoul. The purpose of this study is two folds: First, we analyze the image of Seoul by applying the technology of image mining with the photos uploaded on Flickr by tourists. Second, we draw some significant sightseeing factors by region of attraction where tourists prefer to visit within Seoul.

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Zitierform:

Kim, Dongeun / Kang, Youngok / Park, Yearim / et al: Analysis of Tourists’ Image of Seoul with Geotagged Photos using Convolutional Neural Networks. 2019. Copernicus Publications.

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Rechteinhaber: Dongeun Kim et al.

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